Intelligent cropping of images based on multiple interacting variables

ABSTRACT

Methods and systems for intelligently cropping images, including receiving, over a computer network, a source image, and then associating a first identifier tag with a first object in the source image. A cropped image is generated from the source image wherein the cropping is based on the first object. The system and method then notifying a first user that the first identifier tag is associated with the first object in the cropped image, wherein the notification includes the cropped image.

BACKGROUND

The Internet provides access to a wide range of resources with one ofthe fastest growing uses being social media. Social media includesweb-based and mobile-based technologies that provide for interactivedialogues of user-generated content. Such content includes text, photos,videos, magazines, internet forums, weblogs, social blogs, podcasts,rating, geographic tracking, and social bookmarking.

Using social media a user can post a piece of content, e.g., a photo,and within seconds that content is accessible by a large number ofpeople and in some cases over one-hundred million people. Such access toinformation is both exhilarating and also daunting. For example, a photoof a person could get posted to a social media site, which results inthat person receiving a message that they have been tagged in a photo.The message indicates that a photograph that includes their image hasbeen posted to the social media site, but gives no indication as to thecontents of the image. The photo could contain just the single person orinclude other people and other objects. The photographed person has noimmediate indication of the contents of the photo without fartherinvestigation.

BRIEF SUMMARY

Embodiments include systems and methods for intelligently croppingimages for notification in a social media setting where the cropping isbased upon multiple factors. Such factors can include the status of theobject in the image, e.g., owner, poster, tagger, taggee, generalobserver, whether the object is a person, target device, resolution, andother similar factors.

According to an embodiment, a method is presented that provides forintelligently cropping images that includes receiving, over a computernetwork, a captured or source image and then associating a firstidentifier tag with a first object in the source image. The methodcontinues by generating a cropped image from the source image, whereinthe cropping is based on the first object. The method continues bynotifying a first user that the first identifier tag is associated withthe first object in the cropped image and also includes a copy of thecropped image. The source image can be an image obtained from an imagecapture device, e.g., a camera, or it can be a synthetically generatedimage.

According to another embodiment, a method is presented that provides forintelligently cropping images that includes sending a source image to asocial media website and then receives notification that a firstidentifier tag is associated with a first object in the source image.The method also includes that the received notification includesreceiving a cropped image from the source image where the cropping isbased on the first object.

According to another embodiment, a system is provided that includes aprocessor, memory coupled to the processor, an image storage module, anassociation module, an image cropping module, and a notification module.The image storage module stores uploaded source images. The associationmodule associates a first identifier tag with a first object in thesource image. The image cropping module generates a cropped image fromthe source image where the cropping is based on the first object. Thenotification module notifies a first user that the first identifier tagis associated with the first object in the cropped image and alsoincludes a copy of the cropped image in the notification.

Further embodiments, features, and advantages, as well as the structureand operation of the various embodiments are described in detail belowwith reference to accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS/FIGURES

Embodiments are described with reference to the accompanying drawings.In the drawings, like reference numbers may indicate identical orfunctionally similar elements. The drawing in which an element firstappears is generally indicated by the left-most digit in thecorresponding reference number.

FIG. 1 illustrates an example notification in a social media system withand without an intelligently cropped image, according to an embodiment.

FIG. 2 illustrates an intelligent cropping system, according to anembodiment.

FIG. 3 is an example source image illustrating identified objects,according to an embodiment.

FIG. 4 illustrates multiple grouping of the identified objects withinthe source image based on the status of the person or object receiving anotification, according to an embodiment.

FIG. 5 illustrates the cropped images from FIG. 4, according to anembodiment.

FIG. 6 illustrates a source image illustrating size versus detail,according to an embodiment.

FIGS. 7A and 7B illustrates a cropped image of FIG. 6 illustratingplacement of an object in the image, according to embodiments.

FIG. 8 illustrates a composite cropped image, according to anembodiment.

FIG. 9 and FIG. 10 are flowcharts of intelligently cropped imagemethods, according to an embodiment.

FIG. 11 is a diagram of an example computer system in which embodimentscan be implemented.

The accompanying drawings, which are incorporated herein and form partof the specification, illustrate embodiments of the present inventionand, together with the description, further serve to explain theprinciples of the invention and to enable a person skilled in therelevant art(s) to make and use the invention.

DETAILED DESCRIPTION I. Introduction

Embodiments are described herein with reference to illustrations forparticular applications. It should be understood that the invention isnot limited to the embodiments. Those skilled in the art with access tothe teachings provided herein will recognize additional modifications,applications, and embodiments within the scope thereof and additionalfields in which the embodiments would be of significant utility.

What are needed are systems and methods that intelligently cropidentified objects from an image posted in a social media setting, andbased upon criteria and attributes of the identified person or object inthe photo, send the intelligently cropped image with a notification thatthe person has been tagged to the identified person or object.

Social media may refer to any form of internet based communication thatallows for the creation and exchange of user-generated content. Croppingof an image refers to the identification and/or removal of an area of animage. Cropping is typically performed to remove unwanted subjectmaterial from the image to improve the overall composition of the image,to emphasize a certain set of subject matter, or to remove subjectmatter that is undesirable in a particular situation. Cropping is alsoperformed to compensate for different aspect ratios. For example awidescreen 16:9 format may be cropped to a 1:1 ratio for display on amobile device.

The embodiments described herein are referred in the specification as“one embodiment,” “an embodiment,” “an example embodiment,” etc. Thesereferences indicate that the embodiment(s) described can include aparticular feature, structure, or characteristic, but every embodimentdoes not necessarily include every described feature, structure, orcharacteristic. Further, when a particular feature, structure, orcharacteristic is described in connection with an embodiment, it isunderstood that it is within the knowledge of one skilled in the art toaffect such feature, structure, or characteristic in connection withother embodiments whether or not explicitly described.

FIG. 1 illustrates two example notifications possible in a social mediasystem, according to an embodiment of the present invention.Notification 110 illustrates a notification to a user that includes theuser's icon 112 and a message 114. In this example, message 114 informsthe user that “Suzie Q” has posted an image that supposedly includes aphoto that contains an image of the user. In this example message 114includes only text and does not give the user an indication of whatimage has been posted.

Notification 120 illustrates a notification to a user that includes theuser's avatar icon 122 and a message 124, which as in notification 110,notifies the user that “Suzie Q” has posted an image that supposedlyincludes a photo that contains an mage of the user. However,notification 120 also includes a cropped image 126 of the photo thatincludes the supposed image of the user 128. In this manner the user isable to quickly identify the actual photo that was posted.

II. System Overview

FIG. 2 illustrates an intelligent cropping system 200, according to anembodiment. Intelligent cropping system 200 includes an image storagedevice 210, a recognition module 220, an association module 230, animage cropping module 240, and a notification module 250.

Image data is received and stored in image storage device 210 where theimage data can exist in any defined image format, for example, jpg, bmp,exif, tiff, raw, png, gif, ppm, pgm, pbm, pnm, cgm, svg, pns, jps, ormpo, or any other format, whether the image is two dimensional or threedimensional. Image data storage device 210 may exist as a standalonedevice or be integrated into another device such as a mobilecommunications device, digital camera, or any other image capturedevice.

Recognition module 220 analyzes a source image to identify objectsand/or people within the image. Recognition can include not onlyidentifying a person, or a person's face, but can also compare theidentified features to a feature database (not shown) to identify a nameassociated with the face. In the same manner, recognition module 220 canidentify objects within the image and through a feature database torecognize various logos, e.g., a canned beverage is a Coca-Cola brandedproduct. Objects can be anything, such as an animal, a brand, a plant,etc.

Association module 230 uses the analysis of recognition module 220 toassociate an identifier tag with an identified object or person withinthe source image. Association module 230 can generate multipleidentifier tags to be associated with multiple objects and/or personswithin an image. Association module 230 may also generate tags basedupon the affinity of the recipient to the object in question. Forexample, if the source image contains a Coke can and the recipient hadpreviously post about soda or Coke, then Association module 230 can tagthat object.

Image cropping module 240 intelligently crops the source image based onthe objects and/or people identified by recognition module 220 andassociations made by association module 230. In an embodiment, imagecropping module 240 intelligently and automatically crops the sourceimage based and generates a composite image containing the identifiedpeople/objects. In another embodiment, a user will perform the functionsof recognition module 220 and association module 230 by identifying andassociating a person or object of interest. Alternatively, asemi-automatic approach can be implemented that uses both recognitionmodule 220 and association module 230 and further allows a user toprovide, revise, update, or confirm recognized objects and/or peopleidentified and associations made.

Image cropping module 240 will then crop the image based on theidentification and association performed either by system 200 or a user.The methodology behind the cropping of the image will be discussed infurther detail later.

Notification module 250 notifies the person or object that wasassociated with an identifier tag of the existence of the cropped imageand that the associated person or object exists within the croppedimage. Notification module 250 also delivers a copy of the cropped imageto the associated person or object.

III. Captured/Associated Image

FIG. 3 is an example source image 310, according to an embodiment.Source image 310 includes both objects and people. For example, sourceimage 310 includes person 320, person 330 and person 340. Source image310 also includes objects 350 and 360, where object 350 is a tree andobject 360 is a beverage can.

The people and objects in source image 310 can either manually orautomatically, using a computer-based system, be recognized. Persons320, 330 and 340 can be automatically recognized and thus associatedwith an identifier tag using a facial recognition system, or manually byanother person. Objects, such as object 360, can be recognized, andassociated with an identifier tag based on shape, character recognition,or by logo. Objects, such as object 350, can likewise be identified as atree, either automatically or manually.

IV. Intelligent Cropping

FIG. 4 is an example source image 410 with multiple intelligent croppedareas, according to an embodiment. Source image 410 includes bothobjects and people that have been identified and associated with anidentifier tag. Intelligent cropping is based on a set of pre-definedrules consistent with a social media website that would guide theactions of image cropping module 240. For example, the person that tookimage 410 is considered the owner of the image. The owner has access toall of the images contained within image 410. However, for example, ifthe owner posts image 410 to a social media website and a third partyrecognizes one of the individuals in the image, e.g., person 320, thenperson 320 would receive a notification that they have been tagged in aphoto. Intelligent cropping system 200 would create an intelligentlycropped image that would only include cropped area 420 that includesperson 320. In another embodiment, the cropped area would include theperson 320 and an amount of area around person 320 to give some contextas to the location or situation surrounding person 320.

In another embodiment, the cropped area would include the person 320 andan amount of area around person 320 to give some context as to thelocation or situation surrounding person 320. In general, cropping ofthe image is necessary as there is not enough space to display theentire image in the summary view of the notification. Therefore, thepriority is to notify the user that they have been tagged and limit theimage to include only person 320. In an embodiment, the owner of thephoto receives a notification that includes a composite image includingimages of everyone that has been tagged. In another embodiment, theuser's notification would include a composite image that includes imageof everyone that has been tagged.

In a similar manner, intelligent cropping system 200 generates a numberof additional cropped areas of image 410 in response to rules regardinga social media website. (FIG. 5 illustrates the finished cropped imagesassociated with the images in FIG. 4, according to an embodiment.)

Intelligent cropping system 200 uses pre-defined rules to crop an imagethat are based on an image's resolution, aspect ratio, pixel size anddensity of a sending and receiving display device. In addition, therules can be based on the identity of the view, their relationship tothe objects or people in the image, who owns the image, the actors inthe image, and the identity of the person who tagged an object or personin the image.

In an embodiment, the rules that control access to the content of thecomposite image include the following rules R1-RX. For rules R1-RX, thefollowing terms apply: A “poster” is a person who posts an image to thesocial networking system. This poster may or may not be the copyrightholder of the image. A poster can also be referred to as an “owner” asdiscussed above. A “connected third-party” is a person who is connectedto the poster in the social networking system. An “unconnectedthird-party” is person who is not connected to the poster in the socialnetworking system.

Rules R1-RX are non-limiting and intended to be illustrative. RulesR1-RX are listed below:

R1. When a poster posts an image, that person can view all parts of theimage. For example all tagged people in an image are visible to theposter of the image without restriction.

R2. When an image is posted to a social media website, any third partycan identify and tag another third party in the image.

R3. When a third party within a posted image has been identified andtagged, the poster of the image is notified. This notification to theposter includes the identity of the third party that performed theidentification and tagging

R4. When a third party is tagged in an image, a notification will besent to the third party. Optionally, this notification includes anindication of other tagged third parties in the image.

R5. In a variation of R4, when a third party is tagged in an image,within the notification to the tagged third party, a composite image isprovided that includes images of other tagged third parties in theimage. Optionally, only people or objects who are connected to thetagged third party are included in the notification. Therefore, a taggedthird party will receive a composite image of another tagged thirdparties or objects to whom they are connected in the social mediawebsite.

R6. When a search is performed, a posted image with tagged third partiesand/or objects can be provided as a result in a list of results. Theresults of a search generates a composite image that includes thesearched upon object or third party.

As would be appreciated by one having skill in the relevant art(s),rules R1-RX can be used individually or in combination. Fewer oradditional rules can be used by different embodiments.

Given the above rules, the following scenarios describe possiblescenarios used by intelligent cropping system 200, and image croppingmodule 240:

Scenario #1

-   -   Owner captures image 410 and posts it to a social media website    -   Third party person A recognizes persons 320, 330, and 340 in the        posted photo and tags persons 320, 330, and 340    -   Owner receives a notification that third party person A has        tagged persons 320, 330, and 340. Intelligent cropping system        200 creates cropped image 440 that includes all three tagged        people's faces with an appropriate, based on an analysis of the        image composition, amount of additional image. Cropped image 540        illustrates the result. The notification also includes a copy of        the cropped image, in this example, cropped image 540, which, in        an embodiment is depicted as notification 120 in FIG. 1.    -   Person 320 will receive a notification that she has been tagged        in a photo where intelligent cropping system 200 creates cropped        image 420 that includes her face and the immediate area around        her, which could also include other adjacent faces. In addition,        the notification can include the names of other people or things        that are also tagged in the same photo. Cropped image 520        illustrates the result.    -   Person 330 will receive a notification that he has been tagged        in a photo where intelligent cropping system 200 creates cropped        image 432 that includes only his face and the immediate area        around him. Cropped image 532 illustrates the result.    -   Person 340 will receive a notification that he has been tagged        in a photo where intelligent cropping system 200 creates cropped        image 434 that includes only his face and the immediate area        around him. Cropped image 534 illustrates the result.

Scenario #2

-   -   Owner captures image 410 and posts it to a social media website    -   Third party person B receives a post that persons 330 and 340        have been tagged. Third party person B is connected with persons        330 and 340, but not with person 320. Intelligent cropping        system 200 creates a cropped image 430 that includes only        persons 330 and 340, not person 320. Cropped image 530        illustrates the result.

Scenario #3

-   -   Owner captures image 410 and posts it to a social media website    -   Third party person C enters a search for an image that includes        a tree. Intelligent cropping system 200 creates a cropped image        450 that includes only cropped area 450 of the tree. Cropped        image 550 illustrates the result.

Scenario #4

-   -   Owner captures image 410 and posts it to a social media website    -   Third party person D enters a search for an image that includes        a “brand name.” Intelligent cropping system 200 creates a        cropped image 450 that includes only cropped area 460 showing        the brand name beverage can. Cropped image 560 illustrates the        result.

Intelligent image cropping is also performed based on environmentalfactors such as display characteristics of the receiving device. Forexample, a source image in a 16:9 format, when displayed on ascreen/device with a 4:3 format would be cropped accordingly to conformwith the display characteristics of the receiving device. In a similarfashion, the cropped image would also be adjusted according to screendensity, or resolution of the source image, to allow for the appropriatedisplay of a cropped image.

FIG. 6 is an example source image 610 of a large tree 630 and a smallerperson 620 to illustrate size of the image versus clarity, according toan embodiment. Some scenarios in a social media website allow for theposting of a scaled photo, without being cropped. FIG. 6 is an examplewhere if the full size image is scaled down then the detail in person620 will possibly be lost as the image of person 620 would be verysmall. For example, an original source image could consist of a 5000pixel by 2000 pixel image, which if reduced to a 16 pixel by 16 pixelprofile image, will lose most of the detail contained in the originalimage. Intelligent cropping system 200, in order to preserve some of thedetail of the image of person 620 will crop the image, for example, asshown in FIG. 7A, according to an embodiment. Note that the overallshape of cropped image 710 is preserved from source image 610. Theviewer of cropped image 710 can see the detail of person 720 in additionto noting that person 720 is located at the right edge of the picture,just as he was located in source image 610. In an another embodiment, acombination of cropping and scaling is used whereby the image detail ismaintained and some amount of cropping is also used. Such an example isshown in FIG. 7B where person 720 is viewable with most of the detailcontained in the original image being retained, but also with a scaleddown view of large tree 630.

In an embodiment, if the source image only contains a portion of adesired object, e.g., one side of a person's face, a facial recognitionsystem can be used to identify the person associated with the face,given that enough facial information was available in the source image.Intelligent cropping system 200 could then substitute a different sourceimage of the identified person, e.g., an image containing the entireface of the identified person from image storage device 210.

FIG. 8 is an example of composite cropping in cropped image 810,according to an embodiment. In the case of a source image that consistsof multiple images, where if cropped to only include the desired imageswould result in the person's face or the object of interest beingsmaller than a set threshold, or in a cropped image that is no smallerthan the source image, intelligent cropping system 200 will generate acomposite image, such as is shown in composite image 810. Such an imageretains the detail of each desired subject, e.g., persons 820, 830 and840, but loses the spatial relationship placement between the images inthe source image. However, a notification that is sent in a social mediasystem still conveys to the recipient the nature of the photo thatincludes the other identified people and/or objects in the source image.

V. Methods

Methods in accordance with embodiments will be described with respect tothe intelligent cropping system and methodologies described in FIGS.1-8.

FIG. 9 is a flowchart of an exemplary method 900 for intelligentcropping of image, according to an embodiment of the present invention.For ease of explanation, method 900 is described with respect tointelligent cropping system 200 of FIG. 2 using the methodologydescribed in FIGS. 1 and 3-8, but embodiments of the method are notlimited thereto.

Method 900 starts with step 902 that includes receiving, over a computernetwork, a source image. In an embodiment, intelligent cropping system200 receives and stores a source image in image storage device 210 wherethe image data can exist in any defined image format. Method 900continues to step 904 by associating a first identifier tag with a firstobject in the source image. In an embodiment, recognition module 220 ofintelligent cropping system 200 analyzes a source image to identifyobjects and/or people within the image. Association module 230 ofintelligent cropping system 200, using the analysis or recognitionmodule 220, associates an identifier tag with an identified object orperson with the source image. A source image can contain multiple peopleand/or objects and thus contain multiple identifier tags.

Method 900 continues to step 906 by generating a cropped image from thesource image, wherein the cropping is based on the first object. In anembodiment, image cropping module 240 intelligently crops the sourceimage based on the identified objects and/or people from recognitionmodule 220 and association module 230 of intelligent cropping system200. In an embodiment, a user may perform the functions of recognitionmodule 220 and association module 230 by identifying and associated aperson or object of interest. Whether the person/object is tagged withan identifier by a person or intelligent cropping system 200, imagingcropping module 240 crops the image based on pre-defined rules asdiscussed above.

Method 900 continues to step 908 by notifying a first user that thefirst identifier tag is associated with the first object in the croppedimage wherein the notification includes the cropped image. In anembodiment, notification module 250 notifies the person or object thatwas associated with an identifier tag by recognition module 220 andassociation module 230 of the existence of the cropped image. Thenotification also includes a copy of the cropped image. In addition, thecropped image may also include multiple people and/or objects based onthe pre-defined rules that govern which objects/people are to be shownin the intelligently cropped image. For example, as discussed above whenan owner receives a notification that a third party person has taggedpersons 320, 330, and 340. Intelligent cropping system 200 createscropped image 440 that includes all three tagged people's faces with aminimum of additional image. Method 900 then concludes.

FIG. 10 is a flowchart of an exemplary method 1000 for intelligentcropping of image, according to an embodiment of the present invention.For ease of explanation, method 1000 is described with respect tointelligent cropping system 200 of FIG. 2 using the methodologydescribed in FIGS. 1 and 3-8, but embodiments of the method are notlimited thereto.

Method 1000 starts with step 1002 by receiving a notification that afirst identifier tag is associated with a first object in the sourceimage. In an embodiment, referring to scenario #1, after the ownersubmits source image 410 to a social media website, the owner receives anotification that a third party person has tagged persons 320, 330 and340. Method 1000 continues to step 1004 wherein the notificationincludes receiving a cropped image from the source image wherein thecropping is based on the first object. In an embodiment, referring toscenario #1, the owner receives the notification where the notificationalso includes a copy of the cropped image, in this example, croppedimage 540, which, in an embodiment is depicted as notification 120 inFIG. 1.

VI. Example Computer System Implementation

Aspects of the present invention shown in FIGS. 1-10, or any part(s) orfunction(s) thereof, may be implemented using hardware, softwaremodules, firmware, tangible computer readable media having instructionsstored thereon, or a combination thereof and may be implemented in oneor more computer systems or other processing systems.

FIG. 11 illustrates an example computer system 1100 in which embodimentsof the present invention, or portions thereof, may be implemented ascomputer-readable code. For example, system 200 may be implemented incomputer system 1100 using hardware, software, firmware, tangiblecomputer readable media having instructions stored thereon, or acombination thereof and may be implemented in one or more computersystems or other processing systems. Hardware, software, or anycombination of such may embody any of the modules and components inFIGS. 1-7.

If programmable logic is used, such logic may execute on a commerciallyavailable processing platform or a special purpose device. One ofordinary skill in the art may appreciate that embodiments of thedisclosed subject matter can be practiced with various computer systemconfigurations, including multi-core multiprocessor systems,minicomputers, mainframe computers, computer linked or clustered withdistributed functions, as well as pervasive or miniature computers thatmay be embedded into virtually any device.

For instance, at least one processor device and a memory may be used toimplement the above described embodiments. A processor device may be asingle processor, a plurality of processors, or combinations thereof.Processor devices may have one or more processor “cores.”

Various embodiments of the invention are described in terms of thisexample computer system 1100. After reading this description, it willbecome apparent to a person skilled in the relevant art how to implementthe invention using other computer systems and/or computerarchitectures. Although operations may be described as a sequentialprocess, some of the operations may in fact be performed in parallel,concurrently, and/or in a distributed environment, and with program codestored locally or remotely for access by single or multi-processormachines. In addition, in some embodiments the order of operations maybe rearranged without departing from the spirit of the disclosed subjectmatter.

Processor device 1104 may be a special purpose or a general purposeprocessor device. As will be appreciated by persons skilled in therelevant art, processor device 1104 may also be a single processor in amulti-core/multiprocessor system, such system operating alone, or in acluster of computing devices operating in a cluster or server farm.Processor device 1104 is connected to a communication infrastructure1106, for example, a bus, message queue, network, or multi-coremessage-passing scheme.

Computer system 1100 also includes a main memory 1108, for example,random access memory (RAM), and may also include a secondary memory1110. Secondary memory 1110 may include, for example, a hard disk drive1112, removable storage drive 1114. Removable storage drive 1114 maycomprise a floppy disk drive, a magnetic tape drive, an optical diskdrive, a flash memory, or the like. The removable storage drive 1114reads from and/or writes to a removable storage unit 1118 in awell-known manner. Removable storage unit 1118 may comprise a floppydisk, magnetic tape, optical disk, etc. which is read by and written toby removable storage drive 1114. As will be appreciated by personsskilled in the relevant art, removable storage unit 1118 includes acomputer usable storage medium having stored therein computer softwareand/or data.

Computer system 1100 (optionally) includes a display interface 1102(which can include input/output devices such as keyboards, mice, etc.)that forwards graphics, text, and other data from communicationinfrastructure 1106 (or from a frame buffer not shown) for display ondisplay unit 1130.

In alternative implementations, secondary memory 1110 may include othersimilar means for allowing computer programs or other instructions to beloaded into computer system 1100. Such means may include, for example, aremovable storage unit 1122 and an interface 1120. Examples of suchmeans may include a program cartridge and cartridge interface (such asthat found in video game devices), a removable memory chip (such as anEPROM, or PROM) and associated socket, and other removable storage units1122 and interfaces 1120 which allow software and data to be transferredfrom the removable storage unit 1122 to computer system 1100.

Computer system 1100 may also include a communications interface 1124.Communications interface 1124 allows software and data to be transferredbetween computer system 1100 and external devices. Communicationsinterface 1124 may include a modem, a network interface (such as anEthernet card), a communications port, a PCMCIA slot and card, or thelike. Software and data transferred via communications interface 1124may be in the form of signals, which may be electronic, electromagnetic,optical, or other signals capable of being received by communicationsinterface 1124. These signals may be provided to communicationsinterface 1124 via a communications path 1126. Communications path 1126carries signals and may be implemented using wire or cable, fiberoptics, a phone line, a cellular phone link, an RF link or othercommunications channels.

In this document, the terms “computer program medium” and “computerusable medium” are used to generally refer to media such as removablestorage unit 1118, removable storage unit 1122, and a hard diskinstalled in hard disk drive 1112. Computer program medium and computerusable medium may also refer to memories, such as main memory 1108 andsecondary memory 1110, which may be memory semiconductors (e.g. DRAMs,etc.).

Computer programs (also called computer control logic) are stored inmain memory 1108 and/or secondary memory 1110. Computer programs mayalso be received via communications interface 1124. Such computerprograms, when executed, enable computer system 1100 to implement thepresent invention as discussed herein. In particular, the computerprograms, when executed, enable processor device 1104 to implement theprocesses of the present invention, such as the stages in the methodillustrated by flowcharts 900 of FIG. 9 and 1000 of FIG. 10 as discussedabove. Accordingly, such computer programs represent controllers of thecomputer system 1100. Where the invention is implemented using software,the software may be stored in a computer program product and loaded intocomputer system 1100 using removable storage drive 1114, interface 1120,and hard disk drive 1112, or communications interface 1124.

Embodiments of the invention also may be directed to computer programproducts comprising software stored on any computer useable medium. Suchsoftware, when executed in one or more data processing device, causes adata processing device(s) to operate as described herein. Embodiments ofthe invention employ any computer useable or readable medium. Examplesof computer useable mediums include, but are not limited to, primarystorage devices (e.g., any type of random access memory), secondarystorage devices (e.g., hard drives, floppy disks, CD ROMS, ZIP disks,tapes, magnetic storage devices, and optical storage devices, MEMS,nanotechnological storage device, etc.).

VII. Conclusion

Embodiments described herein provide methods and apparatus for theautomatic cropping of images. The summary and abstract sections may setforth one or more but not all exemplary embodiments of the presentinvention as contemplated by the inventors, and thus, are not intendedto limit the present invention and the claims in any way.

The embodiments herein have been described above with the aid offunctional building blocks illustrating the implementation of specifiedfunctions and relationships thereof. The boundaries of these functionalbuilding blocks have been arbitrarily defined herein for the convenienceof the description. Alternate boundaries may be defined so long as thespecified functions and relationships thereof are appropriatelyperformed.

The foregoing description of the specific embodiments will so fullyreveal the general nature of the invention that others may, by applyingknowledge within the skill of the art, readily modify and/or adapt forvarious applications such specific embodiments, without undueexperimentation, without departing from the general concept of thepresent invention. Therefore, such adaptations and modifications areintended to be within the meaning and range of equivalents of thedisclosed embodiments, based on the teaching and guidance presentedherein. It is to be understood that the phraseology or terminologyherein is for the purpose of description and not of limitation, suchthat the terminology or phraseology of the present specification is tobe interpreted by the skilled artisan in light of the teachings andguidance.

The breadth and scope of the present invention should not be limited byany of the above-described exemplary embodiments, but should be definedonly in accordance with the claims and their equivalents.

1-24. (canceled)
 25. A computer-implemented method comprising:associating an identifier tag with a first object in a source image;automatically generating a first cropped image from the source image toinclude the first object from the source image based on one or morepre-defined rules; automatically generating a second cropped image fromthe source image to include a second object from the source image;automatically scaling the second cropped image to generate a scaledcropped image of the second object; adding the scaled cropped image intothe first cropped image; and after the adding, transmitting to a firstuser a notification that the identifier tag is associated with the firstobject in the source image, wherein the notification includes the firstcropped image.
 26. The method of claim 25, comprising retrieving thesource image over a computer network from an image storage deviceassociated with a social media website to which the first user postedthe source image.
 27. The method of claim 26, comprising transmittingthe notification to a second user, wherein the second user has anaffinity for the first object or the second user is the first object.28. The method of claim 25, wherein the associating comprisescomputer-based recognition of the first object in the source image, andwherein the notification includes a request that the first user toconfirm the computer-based recognition of the first object.
 29. Themethod of claim 25, wherein the associating comprises computer-basedrecognition of the first object in the source image, and wherein themethod further comprises transmitting the notification to a second userassociated with the first object by the computer-based recognition,wherein the notification includes a request that the second user toconfirm the computer-based recognition of the first object.
 30. Themethod of claim 29, wherein the computer-based recognition employs afeature database to recognize the first object as a logo, and whereinthe second user is associated with the logo.
 31. The method of claim 25,wherein the one or more pre-defined rules are based on at least onesocial media relationship to the first object in a social network. 32.The method of claim 25, wherein the associating comprises receiving theidentifier tag.
 33. A system comprising a network interface and anon-transitory machine-readable medium including instructions that whenoperated upon by a machine cause the machine to: associate an identifiertag with a first object in a source image; generate a first croppedimage from the source image to include the first object from the sourceimage based on one or more pre-defined rules; generate a second croppedimage from the source image to include a second object from the sourceimage; scale the second cropped image to generate a scaled cropped imageof the second object; and transmit, from the network interface, to afirst user a notification that the identifier tag is associated with thefirst object in the source image, wherein the notification includes thefirst cropped image and wherein the first cropped image comprises thescaled cropped image.
 34. The system of claim 33, wherein theinstructions further cause the machine to retrieve the source image overa computer network from an image storage device associated with a socialmedia website to which the first user posted the source image.
 35. Thesystem of claim 34, wherein the instructions further cause the machineto transmit, from the network interface, the notification to a seconduser, and wherein the second user has an affinity for the first objector the second user is the first object.
 36. The system of claim 33,wherein the instructions that cause the machine to associate theidentifier tag with the first object cause the machine to performcomputer-based recognition of the first object in the source image, andthe notification includes a request that the first user to confirm thecomputer-based recognition of the first object.
 37. The system of claim33, wherein the instructions that cause the machine to associate theidentifier tag with the first object cause the machine to: performcomputer-based recognition of the first object in the source image; andtransmit, from the network interface, the notification to a second userassociated with the first object by the computer-based recognition,wherein the notification includes a request that the second user toconfirm the computer-based recognition of the first object.
 38. Thesystem of claim 37, wherein the instructions that cause the machine toperform computer-based recognition cause the machine to employ a featuredatabase to recognize the first object as a logo, and the second user isassociated with the logo.
 39. The system of claim 33, wherein the one ormore pre-defined rules are based on at least one social mediarelationship to the first object in a social network.
 40. Anon-transitory computer-readable medium storing a computer programincluding instructions that, when executed by at least one processor,cause the at least one processor to: associate an identifier tag with afirst object in a source image; automatically generate a first croppedimage from the source image to include the first object from the sourceimage based on one or more pre-defined rules; automatically generate asecond cropped image from the source image to include a second objectfrom the source image; automatically scale the second cropped image togenerate a scaled cropped image of the second object; add the scaledcropped image into the first cropped image; and transmit to a first usera notification that the identifier tag is associated with the firstobject in the source image, wherein the notification includes the firstcropped image after the scaled cropped image is added into the firstcropped image.
 41. The non-transitory computer-readable medium of claim40, wherein the instructions cause the at least one processor toretrieve the source image over a computer network from an image storagedevice associated with a social media website to which the first userposted the source image.
 42. The non-transitory computer-readable mediumof claim 41, wherein the instructions cause the at least one processorto transmit the notification to a second user, and the second user hasan affinity for the first object or the second user is the first object.43. The non-transitory computer-readable medium of claim 40, wherein theinstructions that cause the at least one processor to associate theidentifier tag with the first object cause the at least one processor toperform computer-based recognition of the first object in the sourceimage, and the notification includes a request that the first user toconfirm the computer-based recognition of the first object.
 44. Thenon-transitory computer-readable medium of claim 40, wherein: theinstructions that cause the at least one processor to associate theidentifier tag with the first object cause the at least one processor toperform computer-based recognition of the first object in the sourceimage; the instructions cause the at least one processor to transmit thenotification to a second user associated with the first object by thecomputer-based recognition; and the notification includes a request thatthe second user to confirm the computer-based recognition of the firstobject.